• Journal of the Korea Society of Computer and Information
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• v.19 no.7
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• pp.103-111
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• 2014

This paper proposes a modified algorithm that improves on Dijkstra's algorithm by applying it to purely two-way traffic paths, given that a road where bi-directional traffic is made possible shall be considered as an undirected graph. Dijkstra's algorithm is the most generally utilized form of shortest-path search mechanism in GPS navigation system. However, it requires a large amount of memory for execution for it selects the shortest path by calculating distance between the starting node and every other node in a given directed graph. Dijkstra's algorithm, therefore, may occasionally fail to provide real-time information on the shortest path. To rectify the aforementioned shortcomings of Dijkstra's algorithm, the proposed algorithm creates conditions favorable to the undirected graph. It firstly selects the shortest path from all path vertices except for the starting and destination vertices. It later chooses all vertex-outgoing edges that coincide with the shortest path setting edges so as to simultaneously explore various vertices. When tested on 9 different undirected graphs, the proposed algorithm has not only successfully found the shortest path in all, but did so by reducing the time by 60% and requiring less memory.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.7
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• pp.893-900
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• 2007

This paper suggests an algorithm that improves the disadvantages of the Dijkstra algorithm that is commonly used in GPS navigation system, searching for the shortest path. Dijkstra algorithm, first of all, requires much memory for the performance of the algorithm. It has to carry out number of node minus 1, since it determines the shortest path from all the nodes in the graph, starting from the first node. Therefore, Dijkstra algorithm might not be able to provide the information on every second, searching for the shortest path between the roads of the congested city and the destination. In order to solve these problems, this paper chooses a method of searching a number of nodes at once by means of choosing the shortest path of all the path nodes (select of minimum weight arc in-degree and out-degree), excluding the departure and destination nodes, and of choosing all the arcs that coincide with the shortest path of the path nodes, from all the node outgoing arcs starting from the departure node. On applying the suggested algorithm to 14 various digraphs, we succeeded to search the shortest path. In addition, the result was obtained at the speed of 2 to 3 times faster than that of Dijkstra algorithm, and the memory required was less than that of Dijkstra algorithm.

• Journal of Mechanical Science and Technology
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• v.18 no.1
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• pp.92-105
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• 2004

A new algorithm for planning a collision-free path based on algebraic curve is developed and the concept of collision-free Path Space (PS) is introduced. This paper presents a Geometry Mapping (GM) based on two straight curves in which the intermediate connection point is organized in elliptic locus ($\delta$, $\theta$). The GM produces two-dimensional PS that is used to create the shortest collision-free path. The elliptic locus of intermediate connection point has a special property in that the total distance between the focus points through a point on ellipse is the same regardless of the location of the intermediate connection point on the ellipse. Since the radial distance, a, represents the total length of the path, the collision-free path can be found as the GM proceeds from $\delta$=0 (the direct path) to $\delta$=$\delta$$\_$max/(the longest path) resulting in the minimum time search. The GM of elliptic workspace (EWS) requires calculation of interference in circumferential direction only. The procedure for GM includes categorization of obstacles to .educe necessary calculation. A GM based on rectangular workspace (RWS) using Cartesian coordinate is also considered to show yet another possible GM. The transformations of PS among Circular Workspace Geometry Mapping (CWS GM) , Elliptic Workspace Geometry Mapping (EWS GM) , and Rectangular Workspace Geometry Mapping (RWS GM), are also considered. The simulations for the EWS GM on various computer systems are carried out to measure performance of algorithm and the results are presented.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.131-140
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• 2012

The shortest path search algorithm of navigation is generally based on Dijkstra algorithm and considers only the distance using the weight. Dijkstra algorithm based on the distance mainly ought to perform the 'number of nodes 1' and requires a lot of memory, for it is to start from the starting node and to decide the shortest path for all the nodes. Also, it searches only the same identical path in case of any bottleneck due to an accident nearby, since it is based only on the distance, and hence does not have a system that searches the detour road. In order to solve this problem, this paper considers only the travelling time per road (travelling speed * distance), without applying speed criteria (smoothness, slow speed, stagnation and accident control) or road class (express road, national road and provincial road). This provides an advantage of searching the detour, considering the reality that there are differences in time take for the car to travel on different roads with same distance, due to any accident, stagnation, or repair construction. The suggested algorithm proves that it can help us to reach the destination within the shortest time, making a detour from any congested road (outbreak) on providing an information on traveling time continuously(real-time) even though there is an accident in a particular road.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.596-604
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• 2020

Previous studies on pipe auto-routing algorithms generally used such algorithms as A*, Dijkstra, Genetic Algorithm, Particle Swarm Optimization, and Ant Colony Optimization, to satisfy the relevant constraints of its own field and improve the output quality. On the other hand, this study aimed to significantly improve path-finding speed by applying the Jump Point Search (JPS) algorithm, which requires lower search cost than the abovementioned algorithms, for pipe routing. The existing JPS, however, is limited to two-dimensional spaces and can only find the shortest path. Thus, it requires several improvements to be applied to pipe routing. Pipe routing is performed in a three-dimensional space, and the path of piping must be parallel to the axis to minimize its interference with other facilities. In addition, the number of elbows must be reduced to the maximum from an economic perspective, and preferred spaces in the path must also be included. The existing JPS was improved for the pipe routing problem such that it can consider the above-mentioned problem. The fast path-finding speed of the proposed algorithm was verified by comparing it with the conventional A* algorithm in terms of resolution.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.494-497
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• 2022

Recently, the damage caused by flash floods caused by extreme weather due to global warming is increasing. In order to reduce the damage, this paper conducted a study on the search for the shortest route of an evacuation route due to a flash flood. For this, we implemented a route search system using GIS and shape files including buildings and roads and Dijkstra's algorithm. In this study, the location of users close to the point where the flash flood occurs is identified, and the evacuation route is searched from the starting point to the destination point without passing through the dangerous point. Evacuate out of the test bed, or designate a building in the test bed as an evacuation shelter, and search for a route to the nearest evacuation shelter. Accordingly, it is expected that human damage will be reduced by providing the shortest evacuation route.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.5
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• pp.425-433
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• 2012

Dijkstra's algorithm is one of well-known methods to find shortest paths over a network. However, more research on $A^*$ algorithm is necessary to discover the shortest route to a goal point with the heuristic information rather than Dijkstra's algorithm which aims to find a path considering only the shortest distance to any point for an optimal path search. Therefore, in this paper, we compared Dijkstra's algorithm and $A^*$ algorithm for bicycle route selection. For this purpose, the horizontal distance according to slope angle and average speed were calculated based on factors which influence bicycle route selection. And bicycle routes were selected considering the shortest distance or time-dependent shortest path using Dijkstra's or $A^*$ algorithm. The result indicated that the $A^*$ algorithm performs faster than Dijkstra's algorithm on processing time in large study areas. For the future, optimal path selection algorithm can be used for bicycle route plan or a real-time mobile services.

• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.129-137
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• 2010

Currently used shortest path search algorithms involve graphs with vertices and weighted edges between each vertex. However, when finding the shortest path with a randomly shaped obstacle(an island, for instance) positioned in between the starting point and the destination, using such algorithms involves high memory inefficiency and is significantly time consuming - all positions in the map should be considered as vertices and every line connecting any of the two adjacent vertices should be considered an edge. Therefore, we propose a new method for finding the shortest path in such conditions without using weighted graphs. This algorithm will allow finding the shortest obstacle bypass given only the positions of the obstacle boundary, the starting point and the destination. When the row and column size of the minimum boundary rectangle to include an obstacle is m and n, respectively, the proposed algorithm has the maximum time complexity, O(mn). This performance shows the proposed algorithm is very efficient comparing with the currently used algorithms.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.6
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• pp.1-9
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• 2013

The studies on the shortest path algorithms based on Dijkstra algorithm has been done continuously to decrease the time for searching. $A^*$ algorithm is the most represented one. Although fast searching speed is the major point of $A^*$ algorithm, there are high rates of failing in search of the shortest path, because of complex and irregular networks. The failure of the search means that it either did not find the target node, or found the shortest path, witch is not true. This study proposed $A^*$ algorithm applying method that can reduce searching failure rates, preferentially organizing the relations between the starting node and the targeting node, and appling it in reverse according to the organized path. This proposed method may not build exactly the shortest path, but the entire failure in search of th path would not occur. Following the developed algorithm tested in a real complex networks, it revealed that this algorithm increases the amount of time than the usual $A^*$ algorithm, but the accuracy rates of the shortest paths built is very high.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.2
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• pp.454-461
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• 2005

Car navigation system which is killer application fuses map management techniques into CPS techniques. Even if the existing navigation systems are designed for the shortest path, they are not able to cope efficiently with the change of the traffic flow and the bottleneck point of road. Therefore, it is necessary to find out shortest path algorithm based on time instead of distance which takes traffic information into consideration. In this paper, we propose a optimal path search algorithm based on the traffic information. More precisely. we introduce the system architecture for finding out optimal paths, and the limitations of the existing shortest path search algorithm are also analyzed. And then, we propose a new algorithm for finding out optimal path to make good use of the orientation of the collected traffic information.